Artificial Intelligence (AI) is concerned with computing technologies that allow machines to see, hear, talk, think, learn, and solve problems, which is a major influence on the state of education technology today, and the implications are huge. AI has the potential to transform how our education system operates, heighten the competitiveness of institutions, and empower teachers and learners of all abilities. A core of AI in Education technology is knowledge engineering that addresses the acquistion, understanding, description, storage, integration, processing, control, and use of knowledge, among others.
2021 2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021) will be held in Wuhan, China on July 2-4, 2021, aiming for providing a forum for researchers and practitioners involved in different but related domains to confront research results and discuss key problems, giving impetus to high quality research on intelligent systems and cognitive science approaches for educational computing technology applications.
We sincerely invite contributions to 2021 2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021). AIET 2021 conference will take place in Wuhan, China on July 2-4, 2021. Topics of interest for submission include, but are not limited to:
Evaluation: Studies on human learning, cognition, affect, motivation, and attitudes; Design and formative studies of AIED systems; Evaluation techniques relying on computational analyses
Innovative Applications: Domain-specific learning applications (e.g. language, science, engineering, mathematics, medicine, military, industry); Scaling up and large-scale deployment of AIED systems
Intelligent and Interactive Technologies in an Educational Context: Natural language processing and speech technologies; Data mining and machine learning; Knowledge representation and reasoning; Semantic web technologies; Multi-agent architectures; Tangible interfaces, wearables and augmented reality
Intelligent Techniques to Support Disadvantaged Schools and Students, Inequity and Inequality in Education: Socio-economic, gender, and racial issues. Ethics in educational research: sponsorship, scientific validity, participant's rights and responsibilities, data collection, management and dissemination.
Learning Contexts and Informal Learning: Educational games and gamification; Collaborative and group learning; Social networks; Inquiry learning; Social dimensions of learning; Communities of practice; Ubiquitous learning environments; Learning through construction and making; Learning grid; Lifelong, museum, out-of-school, and workplace learning
Modelling and Representation: Models of learners, including open learner models; facilitators, tasks and problem-solving processes; Models of groups and communities for learning; Modelling motivation, metacognition, and affective aspects of learning; Ontological modelling; Computational thinking and model-building; Representing and analyzing activity flow and discourse during learning
Models of Teaching and Learning: Intelligent tutoring and scaffolding; Motivational diagnosis and feedback; Interactive pedagogical agents and learning companions; Agents that promote metacognition, motivation and affect; Adaptive question-answering and dialogue, Educational data mining, Learning analytics and teaching support, Learning with simulations
